ISO FileMaker Magazine

Even in today's interconnected world, you'll still find systems which are so legacy that the only thing you get out of them is some type of output which was popular back in the late 80's and early 90's. One of those formats, which isn't actually an import format, is PCL (Printer Command Language). Yep, there's still a lot of education institutions which will output a PCL file as an export, which is simply just fixed length text with instructions about how a printer should handle the output. It's probably from the heavy use of the good old dot matrix printer days. PCL, however, is used for more than just dot matrix printers.

The great thing about ANY structured content is that you can easily parse and extract exactly what you need from it - so long as you decipher the formatting. PCL, CSV, HTML and JSON - they're all just structured data. This video and its associated file is all about parsing a fixed field length PCL file.

It's a collection of scripts and information about how to go about dynamically parsing a well structured PCL based text file. So, if you're doing development for a business or educational institution, which still only provides PCL output, and you want a clean way to parse the data into your FileMaker solution, then you'll find everything you need to do so successfully and flexibly within the provided file and video.

In the world of serialized data, there's only been a few key technologies and XML was certainly the forerunner. It's been around since the mid 90's and was originally added into FileMaker around version 5 - if memory serves. The implementation of XML/XSLT/XPATH wasn't fully complete with compatible functions and it only works as an import and export feature via the use of an XSLT style sheet.

Learning XSLT and XPATH weren't the easiest things to do and as computing moved forward, so did other technologies. Now, with JSON and JavaScript taking the programming world by storm, we have a new method of serialization and this one is baked into FileMaker.

So, these days, you have the choice of learning xpath and using a plug-in in order to extract data out of XML or you can just convert it into a format such as JSON for simply pulling the data out using FileMaker 16's new JSON functions. With this technique file, and video, you'll be well on your way to extracting data out of XML files if you need to do so.

As with visiting any new country where they speak a different language, if you can’t speak it, then it’s pretty hard to communicate. The same thing applies to intercommunication between technical systems. If you don’t take the time to learn the format being used, then you obviously won’t get very far.

In this video, we take a look at processing JSON from GitHub’s API. It’s one of the last places we’re looking for FileMaker Custom functions. GitHub is a web site which hosts hundreds of thousands of code repositories. These code repositories represent many hundreds of thousands of coding hours. To not take advantage of any pre-existing resources seems a bit silly.

The trick to working with any cloud based resource is to simply learn what questions to ask and how to process the answers you get back. Of course, there’s always that critical piece of know-how which is all about processing the data in the first place. If you’ve never written a recursive FileMaker script, then you’ll certainly see some in action when dissecting the script in this version of our Custom Function database!

With FileMaker’s PatternCount(), Left(), Right() and Middle() functions you can certainly extract a lot of data. The functions, however, are severely limited when it comes to matching variable patterns of data.

That’s where, in the world of programming, Regular Expressions, or RegEx for short, is SUPER handy! It’s used in pretty much EVERY computing language and I don’t personally know a professional developer who can develop without it. It’s been available since the 1950’s and it’s a worthwhile tool to know for sure.

Recently, I personally reduced a complex FileMaker file from three tables and close to twenty dedicated scripts, all for parsing some data, down to one table and two scripts. Trust me, it was a crazy process where a full document of text was imported, line by line, into a FileMaker table, just so a loop could be used to walk across the data multiple times. Talk about extra network traffic just to process some data!

It was MUCH easier to simply use a RegEx pattern and directly extract the data desired and be done with it. Of course, the developer who preceded me obviously didn’t know RegEx and it’s why I’m providing this video for you. Learn it, use it and get the job done quicker when it’s the right tool for the job.

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Users make mistakes. There’s no doubt about that. When given the opportunity, they’ll enter characters and text strings you never expected.

The easy solution to this problem is to simply control the result of what they’ve input. When capturing the input, there may be a variety of rules regarding how you want the data stored.

Do you want to store “4 pm” or 16:00:00? Is the user entering suffixes such as Jr. or Sr. into the last name field or the first name field? Should the input be super simple for an iPad and just happen within one field?

Making the input process easy, yet conforming to your storage rules is often desirable. So is performance! Do you know the performance impacts of that auto-enter calculation versus simply using a script trigger?

This video is all about cleaning up your data input. As a user adds data to the database, you can take the necessary steps to make sure it’s exactly what you want - the low impact way.